Evidence map›Paper›PMID 41559788›Full record

ArticleOrphanet journal of rare diseases2026

Optimizing recruitment in rare disease research: a cross-sectional online study evaluating sampling strategies for hard-to-reach populations.

Shalice Baffour, Bernd Löwe, Annika Braun, Natalie Uhlenbusch

Abstract read
In one paragraph

Article in Orphanet journal of rare diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shalice BaffourDepartment of Psychosomatic Medicine and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Bernd LöweDepartment of Psychosomatic Medicine and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Annika BraunDepartment of Psychosomatic Medicine and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Natalie UhlenbuschDepartment of Psychosomatic Medicine and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. n.uhlenbusch@uke.de.ORCID http://orcid.org/0000-0002-4031-9839

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundResearchers in the field of rare diseases are often confronted with difficulties in achieving sufficiently large sample sizes, given the small case numbers and geographical dispersion of patients. We aimed to evaluate three different sampling strategies that have proven effective for other hard-to-reach populations and compare their effectiveness in the context of rare diseases.

methodsWithin a cross-sectional online study, we compared three sampling strategies (respondent-driven sampling, online-based sampling, and location-based sampling) for their effectiveness in recruiting patients with three rare diseases. Additionally, we compared characteristics of recruited patients. All participants completed an online questionnaire using REDCap. MEASURES: Our primary outcome was the number of patients recruited by each sampling strategy. We further assessed study perception, sociodemographic and clinical characteristics, as well as validated measures to assess depression severity (PHQ-9), anxiety severity (GAD-7), illness cognitions (ICQ), health-related quality of life (SF-12) and psychological burden through somatic symptoms (SSD-12).

resultsA total of N = 254 individuals accessed the survey website and N = 225 completed the sociodemographic characteristics and were included in the analysis. Mean age was 42.53 years (SD = 13.06) and N = 156 (69%) participants were female. Online-based sampling yielded the highest number of participants (N = 184, 82% (95% CI [79%, 85%])), followed by location-based sampling (N = 22, 10% (95% CI [4%, 16%])) and respondent-driven sampling (N = 19, 8% (95% CI [2%, 14%])). Patient characteristics differed significantly regarding gender and satisfaction with medical care, with online-sampling having the highest share of female participants and patients recruited via location-based sampling reporting a higher satisfaction with their overall care. Across all three sampling strategies, participants showed typical features of populations affected by rare diseases such as high rates of depression and anxiety symptoms and reduced quality of life.

conclusionsOur study identified online-based sampling as the most effective recruitment strategy for patients with rare diseases. It may be the most promising approach, especially with limited recruitment periods. Potential biases such as gender imbalances should be considered. We encountered substantial challenges with respondent-driven and location-based sampling. Addressing these challenges in future studies may help to make better use of the potential that lies in these sampling strategies.

Indexed as

Patient SelectionRare DiseasesAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedQuality of LifeSurveys and QuestionnairesLocation-based samplingMedical researchOnline-based samplingPatient recruitmentRare diseasesRespondent-driven samplingSampling strategyVulnerable populations

Identifiers

PMID41559788
PMCPMC12837095

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